Space-time exploration of COVID-19 data and local risk factors in Berlin: the example of the district of Neukölln
Public Health, Healthcare Research, Social and Occupational Medicine
Final Report Abstract
The COVID-19 pandemic poses a global health threat, particularly in urban areas. Understanding the factors influencing the spread of the SARS-COV-2 is crucial for understanding pandemics, designing effective containment, protection and mitigation strategies. To address this, our research project aimed to develop and apply innovative spatiotemporal data analysis techniques to assess, analyse, and monitor the COVID-19 pandemic within an intra-urban setting. In addition, we investigated into the structure of the public health service in order to display advantageous and disadvantageous organisational forms in preventing and containing diseases spreading. We specifically focused on the district Berlin-Neukölln, utilizing reported COVID-19 case data provided by the Neukölln department of health. This district presented an ideal candidate for analysis due to its high temporal and spatial dynamics in reported COVID-19 cases, as well as its diverse population and urban structure. Through our project's research, we discovered that high-risk areas were heterogeneously distributed across the district, with spatial patterns changing across different phases of the pandemic. We identified disease cluster locations at the neighbourhood level, primarily concentrated in specific areas in the northern part of the district. Another key finding of our project was that, in addition to public health and social measures, other factors such as the emergence of virus variants, seasonality, and local events may impacted the incidence of COVID-19 on a small scale. Through our spatial statistical modelling approach, we demonstrated that the impact of different environmental and sociodemographic factors varied throughout different phases of the pandemic, indicating that the underlying mechanisms of disease transmission were not static. We also found that the selected socio-demographic factors had a stronger association and effect on COVID-19 cases compared to environmental factors. In addition, the digitalization level had a strong impact on the data processing work flow and depths of retrospective analysis. In our recent research we identified that protection measures in nursing homes were insufficient during the prevaccine period. We identified some causes overall higher case fatality rates such as nursing homes with higher bed capacities and elderly residents compared to their counterparts living outside of medical settings. The findings of this project demonstrate the importance of analysing place-based health data for developing measures that target vulnerable locations and groups in a spatially and timely manner. This knowledge is essential not only for this pandemic, but, perhaps even more important, for future pandemics and other developments that affect health. Finally, the findings are decisive for identifying underlying inequalities in local health settings and interventions.
Publications
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Raum-zeitliche Exploration von COVID-19 Daten und lokalen Risikofaktoren in Berlin: am Beispiel des Bezirks Neukölln. Das Gesundheitswesen. Georg Thieme Verlag.
Butler, J.; Schmitz, T.; Lambio, C.; Manafa, G.; Savaskan, N. & Lakes, T.
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Raum-zeitliche Exploration von COVID-19 Daten und lokalen Risikofaktoren in Berlin: am Beispiel des Bezirks Neukölln; Kongress Armut und Gesundheit (online); Poster presentation.
Lakes, T., Savaskan, N., Schmitz, T., Lambio, C., Butler, J., Kühl, F. & Georgianna, M.
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Raumzeitliche Exploration von COVID-19 Daten und lokalen Risikofaktoren in Berlin: am Beispiel des Bezirks Neukölln; 17. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi) in Greifswald; September 2022; Oral presentation.
Schmitz, T., Lambio, C., Butler, J., Georgianna, M.; Savaskan, N. & Lakes, T.
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Exploration of the COVID-19 pandemic at the neighborhood level in an intra-urban setting. Frontiers in Public Health, 11.
Schmitz, Tillman; Lakes, Tobia; Manafa, Georgianna; Lambio, Christoph; Butler, Jeffrey; Roth, Alexandra & Savaskan, Nicolai
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Exploring the Spatial Relative Risk of COVID-19 in Berlin-Neukölln. International Journal of Environmental Research and Public Health, 20(10), 5830.
Lambio, Christoph; Schmitz, Tillman; Elson, Richard; Butler, Jeffrey; Roth, Alexandra; Feller, Silke; Savaskan, Nicolai & Lakes, Tobia
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Learning from the COVID-19 pandemic for intra-urban resilience assessments; 2. International Conference on Geographic Information Science (GIScience) in Leeds; September 2023; Poster presentation.
Lakes, T., Manafa, G., Schmitz, T. & Savaskan, N.
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A European roadmap to a digital epidemiology in public health system. Frontiers in Digital Health, 6.
Yavuz, Mesut & Savaskan, Nicolai
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End of the Pandemic - Beginning of Digitalization in the Public Health Service? The German National Funding Program. Gesundheitswesen. 2024 Sep 27.
Yavuz, Mesut & Savaskan, Nicolai
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Epidemiology of COVID-19 in Berlin-Neukölln nursing homes. J Infect Public Health. 2024 Sep 20;17(11):102546.
Roth A., Gehre L., Gerke J., Lutz M., Manafa G., Schmitz T., Lambio C., Zhuang S., Butler J., Lakes T. & Savaskan N.
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German public health reforms draw ire. The Lancet, 403(10428), 714.
Biedermann, Ferry
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Germany's national public health gets reorganized: A new institute shall take center stage. Health Policy, 145, 105084.
Savaskan, Nicolai; Lampl, Benedikt M.J.; Yavuz, Mesut & Tinnemann, Peter
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Neighborhood-level inequalities and influencing factors of COVID-19 incidence in Berlin based on Bayesian spatial modelling. Sustainable Cities and Society, 104, 105301.
Zhuang, Sida; Wolf, Kathrin; Schmitz, Tillman; Roth, Alexandra; Sun, Yukai; Savaskan, Nicolai & Lakes, Tobia
